1. Field of the Invention
The present invention relates generally to techniques for conducting electronic commerce and providing information to consumers deciding whether to enter into commercial transactions. More specifically, tools for incentivizing and aggregating forecasts are applied to the commercial realm, wherein assessments are provided of a buyer's expected satisfaction with a specific good or service, should the customer decide to purchase it.
2. Description of the Related Art
Potential buyers of goods and services often seek out at least two types of information: (1) which particular species of good or service will best suit their needs, and (2) which suppliers of goods and services will provide them the best deal. Obtaining these types of information is costly, but failure to obtain adequate information can lead to consumer dissatisfaction. A variety of tools and resources help to solve each of these problems.
In one conventional approach, rating institutions may assess particular products. For example, users of amazon.com can find information on how satisfied previous consumers have been with particular products. Similarly, readers of Consumer Reports and numerous other publications may obtain information about the quality of particular products, including overall ratings.
A significant limitation of these approaches is that the overall ratings do not generally seek to customize recommendations for particular customers. Individual customers must still expend considerable effort to identify the strengths and weaknesses of each vendor or product to determine whether it will meet the customers' own needs.
In another approach, collaborative filtering technologies have helped to customize recommendations for particular consumers. For example, Netflix.com can recommend particular movies to customers based in part on their evaluation of other movies that they have seen. The collaborative filtering techniques will place more weight in making recommendations for a particular customer on the evaluations of other customers who have similar preferences.
Collaborative filtering technology, however, will not work well for product categories in which past buying history provides few clues about the buyer's needs. A customer's movie preferences will not be of much use in determining which lawnmower a first-time homeowner should buy. In addition, collaborative filtering will not work well for new products, at least so long as there is insufficient data about other users' reactions.
Therefore, in many contexts, customers rely on non-technological sources of information. For example, customers may ask knowledgeable friends about purchases. But sometimes, a customer may not know of or may not have immediate access to any friends who are experts on the relevant area of purchase. And so, many customers rely on advice from salespeople at retail sales establishments to educate themselves about products.
This approach has its own perils, because retail employees' incentives may lead them to seek to achieve goals other than maximizing consumer satisfaction, such as maximizing their employers' profit. Some retail establishments may be able to achieve reputations for providing honest advice, but the equilibrium level of honesty may be lower than the level that, with perfect information, would maximize the joint surplus of the retailer and the consumer.
Meanwhile, feedback mechanisms can help customers decide whether to do business with particular vendors. Customers on eBay.com, for example, can view sellers' “feedback scores.” Sellers with high feedback scores can generally be presumed to be reliable.
Customers, however, must still often choose among many competing vendors with similar feedback profiles. Moreover, the vendors may be less likely to provide advice to customers about which specific products to buy, and so consumers will still need to rely on some other means of identifying a specific product that fits their needs.
Thus, a need continues to exist for providing information to customers about potential purchases, preferably in a way that can overcome at least some of the above problems.